GraphCode-CErl-codesearch safetensors download | Hugging Bay

Q: What is this model?

MatthewsO3/GraphCode-CErl-codesearch is an embedding model for text embeddings published by MatthewsO3, added to Hugging Bay Jun 30, 2026. Model from Hugging Face: MatthewsO3/GraphCode-CErl-codesearch

Q: Can I use it commercially?

It is released under the mit license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.

Q: How big is it?

Hosted here: at least 8 listed files; full count and size unknown. The full repository size is not recorded. The recommended download, model.safetensors, is 498.6 MB.

Q: What can I download here?

Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: unknown. The original release is at https://huggingface.co/MatthewsO3/GraphCode-CErl-codesearch.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 8 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-matthewso3-graphcode-cerl-codesearch/safety on Hugging Bay.

Q: Will MatthewsO3/GraphCode-CErl-codesearch run on my computer?

We can’t check the fit; we don’t know your machine. We don’t have your machine’s specs, so no check ran and no verdict is shown. Answer two quick questions and we’ll estimate, from the memory you tell us, whether it fits your machine. Or skip it; you can still download; fit isn’t checked.

MatthewsO3

GraphCode-CErl-codesearch

MatthewsO3/GraphCode-CErl-codesearch

text embeddingsLicense: mitHashes recordedsafetensors

Content controls: not assessed.

Model from Hugging Face: MatthewsO3/GraphCode-CErl-codesearch

View as JSON →

8 hosted of 9 listed

Hashes recorded. Date not recorded.

File	大小	SHA-256	来源	下载
Weights
`model.safetensors` Default	498.6 MB	`dd9faba2…a0f1e22c` `dd9faba2e723ddbf1f57ffd4672487638f59cb2b0b1a46bcfca5fd8da0f1e22c`	Hosted	下载
Tokenizer & config
`config.json`	683 bytes	`d052e986…50946433` `d052e9865b70a898708f4d13a4f9be85ae473f9f4cb9d41667a966cc50946433`	Hosted	下载
`merges.txt`	456.3 KB	`1ce16647…7726adc5` `1ce1664773c50f3e0cc8842619a93edc4624525b728b188a9e0be33b7726adc5`	Hosted	下载
`tokenizer.json`	3.56 MB	`faf1322b…4d16f4e5` `faf1322b8087991436b7404d8609d66e2068629a648b7d0ddb2145ce4d16f4e5`	Hosted	下载
`tokenizer_config.json`	1.25 KB	`3e524fcb…0361616a` `3e524fcbb3d446afb921a867d6f354e1873d142f4a597aecda076f730361616a`	Hosted	下载
`vocab.json`	798.3 KB	`ed19656e…3670ab5e` `ed19656ea1707df69134c4af35c8ceda2cc9860bf2c3495026153a133670ab5e`	Hosted	下载
`special_tokens_map.json`	957 bytes	`8293ae96…2eb2d4b7` `8293ae960b0a0852d4d3813118030a1149a3ed9fe37bc2e1e7b3c2e62eb2d4b7`	Hosted	下载
Docs
`README.md`	7.23 KB	`948a73d3…171ca737` `948a73d395e2a5ab3b23ac4a6353bc924884d8a8070ac2d441e5028f171ca737`	Hosted	下载
`.gitattributes`	0 bytes	—	Upstream only	File metadata

检查下载文件

In the folder where you saved model.safetensors, run:

macOS

shasum -a 256 -- 'model.safetensors'

Linux

sha256sum -- 'model.safetensors'

Windows

Get-FileHash -LiteralPath 'model.safetensors' -Algorithm SHA256

Compare the result with the recorded SHA-256.

GraphCode-CErl-codesearch

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